“Musk Is Scamming the City of Memphis”: Meet Two Brothers Fighting Colossus, Musk’s xAI Data Center

• “Periodic table of machine learning” could fuel AI discovery

  https://news.mit.edu/sites/default/files/styles/news_article__image_gallery/public/images/202504/MIT_Periodic-Algorithm-01-PRESS_0.jpg?itok=kQ0_0ElK

• Chinese AI Firms Are Reportedly Dumping NVIDIA’s RTX 4090D GPUs Into The Market To Capitalize On The Rising Prices

  It is claimed that the GPU sell-off has occurred because many AI firms are experiencing significantly lower server utilization rates, going as low as 20%. This means that for such businesses to stay profitable, they would need to sell out their extra computing power, which is a major contributor to the sell-off. Apart from this, with the supply chain uncertainty in China following the new US export controls, it is certain that Chinese firms want to capitalize on it the most by selling GPUs at a time when prices are soaring.

  NVIDIA's RTX 4090D 48 GB is going for as high as $6,000 in local markets, and with AI firms now selling their inventory, we do expect it to come down.

• People Worry More About Today’s AI Harms Than Future Catastrophes

  Summary: A new study finds that people are more concerned about the immediate risks of artificial intelligence, like job loss, bias, and disinformation, than they are about hypothetical future threats to humanity. Researchers exposed over 10,000 participants to different AI narratives and found that, while future catastrophes raise concern, real-world present dangers resonate more strongly.

  Key Facts:

  Present > Future: Respondents prioritized concerns like bias and misinformation over existential AI threats.

  No Trade-Off: Awareness of future risks did not reduce concern for today’s real-world AI harms.

  Public Dialogue Needed: People want thoughtful discourse on both immediate and long-term AI challenges.

• AI 2027

  Mid 2025: Stumbling Agents

  Late 2025: The World’s Most Expensive AI

  Early 2026: Coding Automation

  Mid 2026: China Wakes Up

  Late 2026: AI Takes Some Jobs

  January 2027: Agent-2 Never Finishes Learning

  February 2027: China Steals Agent-2

  March 2027: Algorithmic Breakthroughs

  April 2027: Alignment for Agent-3

  May 2027: National Security

  June 2027: Self-improving AI

  September 2027: Agent-4, the Superhuman AI Researcher

• French Startup’s AI Influencer Builder To Take Over OnlyFans, Earning More Than Humans Soon; Internet Is Not Amused

  The AI platform is also expected to seize the adult content platform OnlyFans within a year, as influencers seek to cut short production costs. This shouldn’t come across as a surprise. While several platforms have stringent guidelines for AI-generated content, the deepfakes are evolving and are not restricted to masking the face with someone else’s.

• A columnist suggested dumping your AI lover. We asked AI to respond.

• How can companies keep up with A.I.’s demands?

  “If we look at not just how much of it we’re producing, but the fidelity at which we’re creating it — the megapixel size of the images, as well as the flip to more rich audio and video than text — all of this evolution will change the way we store, manage and protect data,” says Shawn Rosemarin, vice president of Research and Development for Customer Engineering at Pure Storage.

  How can organizations cope with all that data, whether at rest or in transit? Rosemarin says prioritizing efficiency in data platforms is the answer.

  Operational efficiency means fewer people are managing larger amounts of data. Integrated and automated storage platforms that don’t require constant manual intervention are key. “Fewer people turning knobs means more people working on the important stuff and a faster path to real results,” Rosemarin explains.

  Energy efficiency allows for storage growth within an existing power footprint and at reduced operating costs. A.I. is already notoriously power-, cooling- and space-hungry; an energy efficient storage platform helps to ease these operational challenges.

  Performance efficiency means delivering high IOPS and throughput and low latency for both training and inference for A.I. applications. Storage platforms that minimize the need to move large data sets can provide a significant boost in this area.

  Scale efficiency allows organizations to quickly and non-disruptively scale up, adding storage devices to existing arrays, or scale out, adding networked storage nodes, to meet the growing demands of A.I. data and workloads. Efficient scaling must occur transparently eliminating any costly downtime or performance impact.

• China Floods the World With AI Models After DeepSeek’s Success

  OpenAI, for one, is now trying to strike a careful balance. The ChatGPT maker has said it’s mulling giving away some of its technology following DeepSeek’s success with the open-source approach. At the same time, OpenAI is still weighing charging far more for its most sophisticated products.

• Powerful A.I. Is Coming. We’re Not Ready.

  I believe that hardened A.I. skeptics — who insist that the progress is all smoke and mirrors, and who dismiss A.G.I. as a delusional fantasy — not only are wrong on the merits, but are giving people a false sense of security.

  I believe that the right time to start preparing for A.G.I. is now.

  Reasoning models, which include OpenAI’s o1 and DeepSeek’s R1, are trained to work through complex problems, and are built using reinforcement learning — a technique that was used to teach A.I. to play the board game Go at a superhuman level. They appear to be succeeding at things that tripped up previous models. (Just one example: GPT-4o, a standard model released by OpenAI, scored 9 percent on AIME 2024, a set of extremely hard competition math problems; o1, a reasoning model that OpenAI released several months later, scored 74 percent on the same test.)

• Taigi LLMs

  

  This project is based on Traditional Chinese LLaMA-2 models. We continued pre-training with 78MB of Taiwanese Hokkien monolingual corpora, which includes POJ, Hanlo, and Hanzi writing systems, to produce the Taiwanese Hokkien version LLaMA-2 base model, Taigi-Llama-2. We then trained a translation model based on Taigi-Llama-2 using collected parallel datasets to obtain Taigi-Llama-2-Translator.

• A Crucial Debate for AI’s Future

  Elon Musk Defends the Peak Data Theory, Saying There’s No More Human Data to Train AI

  Despite these risks, the allure of synthetic data remains strong for companies like Microsoft, Google, and Anthropic. They’ve already implemented it in models such as Phi-4, Gemma, and Claude 3.5 Sonnet. The central debate now revolves around finding the right balance between real-world and synthetic data. How much of each is appropriate for the ongoing development of AI?

  In the end, it’s about striking the right balance: fostering technological innovation while safeguarding human values. If done right, AI can remain a tool that serves humanity, rather than becoming something that outpaces or overrides our own intelligence.

  

• What is Manus? China's World-First Fully Autonomous AI Agent Explained

  Developed by a low-profile team and backed by Chinese investors and developers, Manus is currently available as an invitation-only web preview. A demonstration video on its website, manus.im, showcases its ability to create a custom website through a step-by-step process.

  Manus is but the latest example of the mania that has swept over China since January, when DeepSeek, the country’s hottest AI start-up, shook the world with a whizzy model that cost a fraction of similarly powerful Western ones to train. The effect on Chinese markets has been staggering. Stocks are experiencing their best start to the year on record. The Hang Seng Tech Index, which tracks the biggest Chinese tech companies listed in Hong Kong, is up by more than 40 per cent since mid-January.

  Many in China are betting that cheaper AI will unlock the door for innovators to design new applications for the technology.

• Microsoft CEO Admits That AI Is Generating Basically No Value

  As of right now, the economy isn't showing much sign of acceleration, and certainly not because of an army of AI agents. And whether it's truly a question of "when" — not "if," as he claims — remains a hotly debated subject.

  There's a lot of money on the line, with tech companies including Microsoft and OpenAI pouring hundreds of billions of dollars into AI. Nadella's podcast appearance could be seen as a way for Microsoft to temper some sky-high expectations, calling for a more rational, real-world approach to measure success.

• As Hype Fades, OpenAI Suddenly Cancels Release of Its Hot Upcoming AI

  In a statement posted on his arch-nemesis Elon Musk's social network, Altman wrote circuitously around the previously slated launch of o3, the latest awkwardly-named version of its frontier reasoning model that's said to sometimes cost more than $1,000 worth of computing power per query.

  "In both ChatGPT and our API, we will release GPT-5 as a system that integrates a lot of our technology, including o3," the CEO said. "We will no longer ship o3 as a standalone model."

  With its claims of self-fact-checking, the launch of o1 last fall indeed got some splash. But it faded quickly — and when's the last time you heard about something actually exciting happening with it?

• Larry E. Encourages World Leaders to Funnel All of Their Data to AI (and Maybe His Data Centers)

  Fragmented sets of data about a population’s health, agriculture, infrastructure, procurement and borders should be unified into a single, secure database that can be accessed by AI models, Ellison said…Countries with rich population data sets, such as the UK and United Arab Emirates, could cut costs and improve public services, particularly health care, with this approach, Ellison said. How convenient, then, that Ellison happens to own a database company that is also currently attempting to scale up its AI business. Interesting how that works!

  You may not like what Ellison has to say but, increasingly, it doesn’t seem like there’s much you can do about it. The new 'Old Donald' administration has made it known that it’s going all-in on the AI industry and that it wants to build out America’s AI businesses to make them the most dominant ones in the world. Ellison’s Oracle was recently announced as a member of the Stargate project, a new AI infrastructure effort that seeks to build AI data centers all across the U.S. Other participating members include OpenAI, Microsoft, SoftBank, NVIDIA, and other powerful tech companies.

• Meta Suspends Book Licensing for AI Training

  The filings are related to the case Kadrey v. Meta Platforms — one of many such cases winding through the U.S. court system that’s pitted AI companies against authors and other intellectual property holders. For the most part, the defendants in these cases — AI companies — have claimed that training on copyrighted content is “fair use.” The plaintiffs — copyright holders — have vociferously disagreed.

• AI Is Infiltrating the U.S. Government

  Tere is reason to believe that Musk may soon pivot to prioritizing his AI ventures, where access to data is as important as computing power. Think about Tesla’s complicated position in China. Recently, its sales in the country were dramatically overtaken by BYD, a young and innovative Chinese EV maker. BYD saw a 41 percent increase in sales in China last year and sold more than five times more vehicles than Tesla there.

  The rise of BYD and other fast-moving Chinese car manufacturers may be convincing Musk that the future of his immense fortune is less tied up in automobiles than in the control of data.

  Musk’s role as Tesla’s CEO also points to numerous potential conflicts of interest. On Feb. 13, news outlets reported that a State Department contract to spend $400 million on armored EVs with Tesla was edited to omit any reference to the company after reports of the contract sparked backlash. There is also the question of Musk’s business in China, where much of Tesla’s manufacturing is based. This week, the company opened a massive $200 million battery factory in Shanghai.

• UK and US refuse to sign international AI declaration

  The statement, signed by France, China and India among other countries, pledges an "open", "inclusive" and "ethical" approach to the technology's development.

  Vance told world leaders that AI was "an opportunity that the 'Old Donald' administration will not squander" and said "pro-growth AI policies" should be prioritised over safety.

• What’s Behind Elon Musk’s Hostile Bid for Control of OpenAI

  Altman says: "No Thanks". Musk says: 'Not interested in buying TikTok

  The tech mogul is unlikely to win. But his goal may be more about making life difficult for the A.I. start-up and its leader, Sam Altman.

  The blockbuster bid complicates things for OpenAI. The start-up is about to close a $40 billion fund-raising deal with SoftBank at a valuation of $300 billion. Altman also is trying to pull off a much-needed plan to convert the nonprofit OpenAI into a for-profit entity.

  A question of the OpenAI board’s duties: Its directors don’t have any fiduciary responsibility to maximize returns, since it’s a charity. Board members include Bret Taylor, who sparred with Musk over his purchase of Twitter, and Larry Summers, the former Treasury secretary, whom Musk criticized just on Monday.

• DeepSeek, Modi and AI: President Macron's Exclusive Conversation with Palki Sharma

• AI Action Summit in Paris

• Why AI makes up stuff

• Why OpenAI Didn’t Use AI To Make Its Super Bowl Ad About AI

• ChatGPT | The Intelligence Age

• OpenAI Considering 'Different Open-Source Strategy'

  Meta Chief AI Scientist Yann LeCun said in a post on LinkedIn that the impact of DeepSeek showed that “Open source models are surpassing proprietary ones.”

  “DeepSeek has profited from open research and open source. … They came up with new ideas and built them on top of other people’s work,” LeCun wrote. “Because their work is published and open source, everyone can profit from it. That is the power of open research and open source.”

  OpenAI’s Quiet Power Play: How Strategic Silence Countered DeepSeek’s Hype

  Meta’s strategy was to distribute open-source AI mod

  DeepSeek, TikTok, Temu: How China is taking the lead in tech

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  Teens aren't buying Big Tech's promises on AI and online safety

  Meta, Apple, and other major technology corporations are investing significant amounts of money to appeal to teens and young users. However, a study by Common Sense Media suggests that their efforts may ultimately be in vain, as a significant portion of US teens have little faith in Big Tech's approach and the role of AI.

  The study explores the relationship between teens, Big Tech companies, and trust in technology, based on a survey of 1,045 teens aged 13 – 18.

  Nearly half (47 percent) of surveyed teens also believe Big Tech will not make responsible decisions about AI and its implementation in their products. Additionally, 39 percent of US teens who have used generative AI for schoolwork reported encountering inaccuracies and misinformation, CSM noted.

  Stop Worshiping the American Tech Giants

  When Chinese artificial intelligence firm DeepSeek shocked Silicon Valley and Wall Street with its powerful new A.I. model, Marc Andreessen, the Silicon Valley investor, went so far as to describe it as “A.I.’s Sputnik moment.” Presumably, Mr. Andreessen wasn’t calling on the federal government to start a massive new program like NASA, which was our response to the Soviet Union’s Sputnik satellite launch; he wants the U.S. government to flood private industry with capital, to ensure that America remains technologically and economically dominant.

  As an antitrust enforcer, I see a different metaphor. DeepSeek is the canary in the coal mine. It’s warning us that when there isn’t enough competition, our tech industry grows vulnerable to its Chinese rivals, threatening U.S. geopolitical power in the 21st century.

  It should be no surprise that our big tech firms are at risk of being surpassed in A.I. innovation by foreign competitors. After companies like Google, Apple and Amazon helped transform the American economy in the 2000s, they maintained their dominance primarily through buying out rivals and building anticompetitive moats around their businesses.

  Over the last decade, big tech chief executives have seemed more adept at reinventing themselves to suit the politics of the moment - resistance sympathizers, social justice warriors, MAGA enthusiasts - than on pioneering new pathbreaking innovations and breakthrough technologies.

  Microsoft CFO urges employees to "focus" amid recent AI developments like OpenAI's $500 billion Stargate project — but CEO says DeepSeek is good for business

  Interestingly, Microsoft CEO Satya Nadella sees the emergence of DeepSeek's R1 AI model and other iterations as good for business amid Azure's slow growth rate. According to the executive: AI will be much more ubiquitous. And so, therefore, for a hyperscaler like us and a PC platform provider like us, this is all good news as far as I'm concerned."

  Microsoft integrates DeepSeek’s AI model into Azure and GitHub (Owned by Microsoft).

  OpenAI CEO Sam Altman: Company Considering ‘Different Open-Source Strategy’

  The artificial intelligence (AI) developer had adopted that approach after starting as an open-source company, but is now rethinking it after DeepSeek’s release of a lower cost open-source AI model, Seeking Alpha reported Saturday (Feb. 1), citing OpenAI executives’ comments during a Reddit “Ask Me Anything” event held Friday (Jan. 31).

  OpenAI CEO Sam Altman said during the event that OpenAI needs to “figure out a different open-source strategy,” according to the report.

  Do we need a supercomputer @ home

  OpenAI Asking for Tens of Billions in New Investment to "Fund Its Money-Losing business Operations"

  OpenAI announces surprise ‘Deep Research’ stream tonight(2/2)

  

  The AI lie: how trillion-dollar hype is killing humanity

  But here’s the uncomfortable truth: in the quest for AGI in high-stakes fields like medicine, law, veterinary advice, and financial planning, AI isn’t just “not there yet,” it may never get there.

  These chips are at the center of a tense technological competition between the United States and China. As the U.S. government works to maintain the country’s lead in the global A.I. race, it is trying to limit the number of powerful chips, like those made by Silicon Valley firm Nvidia, that can be sold to China and other rivals.

  And it was created on the cheap, challenging the prevailing idea that only the tech industry’s biggest companies — all of them based in the United States — could afford to make the most advanced A.I. systems. The Chinese engineers said they needed only about $6 million in raw computing power to build their new system. That is about 10 times less than the tech giant Meta spent building its latest A.I. technology.

  

• OpenAI Furious DeepSeek Might Have Stolen All the Data OpenAI Stole From Us

  “Microsoft Corp. and OpenAI are investigating whether data output from OpenAI’s technology was obtained in an unauthorized manner by a group linked to Chinese artificial intelligence startup DeepSeek, according to people familiar with the matter.” The story goes on to say that “Such activity could violate OpenAI’s terms of service or could indicate the group acted to remove OpenAI’s restrictions on how much data they could obtain, the people said.”

  The venture capitalist and new 'Old Donald' administration member David Sacks, meanwhile, said that there is “substantial evidence” that DeepSeek “distilled the knowledge out of OpenAI’s models.”

• OpenAI says Chinese rivals using its work for their AI apps

  Although China has boosted investment in advanced tech to diversify its economy, DeepSeek is not one of the big Chinese firms that have been developing AI models to rival US-made ChatGPT.

  Experts say the US still has an advantage - it is home to some of the biggest chip companies - and that it's unclear yet exactly how DeepSeek built its model and how far it can go.

• China Is Closing the A.I. Gap With the United States - read in harnji (July, 2024)

  While many American companies are worried that A.I. technologies could accelerate the spread of disinformation or cause other serious harm, Chinese companies are more willing to release their technologies to consumers or even share the underlying software code with other businesses and software developers. This kind of sharing of computer code, called open source, allows others to more quickly build and distribute their own products using the same technologies.

  The White House has instituted a trade embargo designed to prevent Chinese companies from using the most powerful versions of computer chips that are essential to building artificial intelligence. A group of lawmakers has introduced a bill that would make it easier for the White House to control the export of A.I. software built in the United States. Others are trying to limit the progress of open-source technologies that have helped fuel the rise of similar systems in China.

  But Chinese tech companies face a major constraint on the development of their A.I. systems: compliance with Beijing's strict censorship regime, which extends to generative A.I. technologies.

• Who is behind DeepSeek and how did it achieve its AI ‘Sputnik moment’?

  “Our principle is not to lose money, nor to make huge profits … our starting point is not to take advantage of the opportunity to make a fortune, but to be at the forefront of technology and promote the development of the entire ecosystem.”

  By 2021, he was reported to have bought 10,000 of the chips, seemingly for his personal hobby. Only a handful of large Chinese tech firms have similar reserves of Nvidia semiconductors. “Many people would think that there is an unknown business logic behind this, but in fact, it is mainly driven by curiosity,” Liang said in 2023.

  Some analysts and investors have expressed scepticism about DeepSeek’s market-rattling claims.

  

• How Chinese A.I. Start-Up DeepSeek Is Competing With Silicon Valley Giants

  But the team behind the system, called DeepSeek-V3, described an even bigger step. In a research paper explaining how they built the technology, DeepSeek’s engineers said they used only a fraction of the highly specialized computer chips that leading A.I. companies relied on to train their systems.

  

• Google has just announced the ability to chain actions in Gemini and it could change the way we use AI for good

  The stand-out feature is Gemini's new ability to chain actions together. This means you can now do things like connect to Google Maps to search for nearby restaurants, then draft a text in Google Messages to send to people you’d like to invite to lunch, all through Gemini commands.

• Musk Pours Cold Water on 'Old Donald'-Backed Stargate AI Project

  Oracle, and Softbank OpenAI’s legal battle with Elon Musk reveals internal turmoil over avoiding AI ‘dictatorship’

  “It’s clear he has abused the proximity to the president,” said the 'Old Donald' ally. “The problem is the president doesn’t have any leverage over him and Elon gives zero fucks.”

• The Pentagon says AI is speeding up its 'kill chain'

  The “kill chain” refers to the military’s process of identifying, tracking, and eliminating threats, involving a complex system of sensors, platforms, and weapons. Generative AI is proving helpful during the planning and strategizing phases of the kill chain, according to Plumb.